scholarly journals Dimensions of the 2020 wildfire catastrophe in the Pantanal wetland: the case of the municipality of Poconé, Mato Grosso, Brazil

2021 ◽  
Vol 10 (15) ◽  
pp. e08101522619
Author(s):  
Vinícius de Freitas Silgueiro ◽  
Carolina Ortiz Costa Franco de Souza ◽  
Eriberto Oliveira Muller ◽  
Carolina Joana da Silva
Keyword(s):  
Water Surface ◽  
Infrared Imaging ◽  
Burned Area ◽  
Mato Grosso ◽  
Fire Emissions ◽  
Active Fire ◽  
Preventive Actions ◽  
Rivers And Lakes ◽  
Climate Crisis ◽  
Pantanal Wetland

In 2020, a total of 3.9 million hectares were burned in the Pantanal biome, which represents approximately 30% of its total area. Of the three existing biomes in the state of Mato Grosso, the Pantanal was the most impacted and, among all the municipalities in Mato Grosso, Poconé had the largest burned area. We aimed to characterize the areas affected by fires in the municipality of Poconé in 2020 to support prevention and adaptation actions in future scenarios. For this, we used the mapping of areas affected by fires made from the detections of active fire collected by the Visible Infrared Imaging Radiometer Suite (VIIRS) sensor and available by the Global Fire Emissions Database (GFED). The results showed that a total of 869,170 hectares were burned in Poconé in 2020. Of this total, 97.3% were in natural areas, viz. forest formations (37%), savanna (2.8%), grassland formations (23.4%), wetlands (29.7%), and vegetation in dried-up rivers and lakes (4.4%). Concerning land categories, almost half of the fires occurred in private rural properties registered in the Rural Environmental Registry (CAR). In this scenario, we highlighted the importance of monitoring fires and holding those responsible for them accountable. It is also important to implement preventive actions in synergy with managers and local communities as a way of adapting to the climate crisis, intense drought, and less water surface available in the region, which increases the risk and damage of fires.

scholarly journals Near Real-Time Automated Early Mapping of the Perimeter of Large Forest Fires from the Aggregation of VIIRS and MODIS Active Fires in Mexico

2020 ◽  
Vol 12 (12) ◽  
pp. 2061 ◽  
Author(s):  
Carlos Ivan Briones-Herrera ◽  
Daniel José Vega-Nieva ◽  
Norma Angélica Monjarás-Vega ◽  
Jaime Briseño-Reyes ◽  
Pablito Marcelo López-Serrano ◽  
...  
Keyword(s):  
Real Time ◽  
Forest Fires ◽  
Large Scale ◽  
Infrared Imaging ◽  
Activity Patterns ◽  
Burned Area ◽  
Management Decision ◽  
Coarse Scale ◽  
Early Evaluation ◽  
Active Fire

In contrast with current operational products of burned area, which are generally available one month after the fire, active fires are readily available, with potential application for early evaluation of approximate fire perimeters to support fire management decision making in near real time. While previous coarse-scale studies have focused on relating the number of active fires to a burned area, some local-scale studies have proposed the spatial aggregation of active fires to directly obtain early estimate perimeters from active fires. Nevertheless, further analysis of this latter technique, including the definition of aggregation distance and large-scale testing, is still required. There is a need for studies that evaluate the potential of active fire aggregation for rapid initial fire perimeter delineation, particularly taking advantage of the improved spatial resolution of the Visible Infrared Imaging Radiometer (VIIRS) 375 m, over large areas and long periods of study. The current study tested the use of convex hull algorithms for deriving coarse-scale perimeters from Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) active fire detections, compared against the mapped perimeter of the MODIS collection 6 (MCD64A1) burned area. We analyzed the effect of aggregation distance (750, 1000, 1125 and 1500 m) on the relationships of active fire perimeters with MCD64A1, for both individual fire perimeter prediction and total burned area estimation, for the period 2012–2108 in Mexico. The aggregation of active fire detections from MODIS and VIIRS demonstrated a potential to offer coarse-scale early estimates of the perimeters of large fires, which can be available to support fire monitoring and management in near real time. Total burned area predicted from aggregated active fires followed the same temporal behavior as the standard MCD64A1 burned area, with potential to also account for the role of smaller fires detected by the thermal anomalies. The proposed methodology, based on easily available algorithms of point aggregation, is susceptible to be utilized both for near real-time and historical fire perimeter evaluation elsewhere. Future studies might test active fires aggregation between regions or biomes with contrasting fuel characteristics and human activity patterns against medium resolution (e.g., Landsat and Sentinel) fire perimeters. Furthermore, coarse-scale active fire perimeters might be utilized to locate areas where such higher-resolution imagery can be downloaded to improve the evaluation of fire extent and impact.

scholarly journals Six global biomass burning emission datasets: intercomparison and application in one global aerosol model

2020 ◽  
Vol 20 (2) ◽  
pp. 969-994 ◽  
Author(s):  
Xiaohua Pan ◽  
Charles Ichoku ◽  
Mian Chin ◽  
Huisheng Bian ◽  
Anton Darmenov ◽  
...  
Keyword(s):  
Southern Hemisphere ◽  
Biomass Burning ◽  
Satellite Observations ◽  
Burned Area ◽  
Aerosol Model ◽  
Fire Emissions ◽  
Active Fire ◽  
Aerosol Emission ◽  
High Level ◽  
Aerosol Emissions

Abstract. Aerosols from biomass burning (BB) emissions are poorly constrained in global and regional models, resulting in a high level of uncertainty in understanding their impacts. In this study, we compared six BB aerosol emission datasets for 2008 globally as well as in 14 regions. The six BB emission datasets are (1) GFED3.1 (Global Fire Emissions Database version 3.1), (2) GFED4s (GFED version 4 with small fires), (3) FINN1.5 (FIre INventory from NCAR version 1.5), (4) GFAS1.2 (Global Fire Assimilation System version 1.2), (5) FEER1.0 (Fire Energetics and Emissions Research version 1.0), and (6) QFED2.4 (Quick Fire Emissions Dataset version 2.4). The global total emission amounts from these six BB emission datasets differed by a factor of 3.8, ranging from 13.76 to 51.93 Tg for organic carbon and from 1.65 to 5.54 Tg for black carbon. In most of the regions, QFED2.4 and FEER1.0, which are based on satellite observations of fire radiative power (FRP) and constrained by aerosol optical depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS), yielded higher BB aerosol emissions than the rest by a factor of 2–4. By comparison, the BB aerosol emissions estimated from GFED4s and GFED3.1, which are based on satellite burned-area data, without AOD constraints, were at the low end of the range. In order to examine the sensitivity of model-simulated AOD to the different BB emission datasets, we ingested these six BB emission datasets separately into the same global model, the NASA Goddard Earth Observing System (GEOS) model, and compared the simulated AOD with observed AOD from the AErosol RObotic NETwork (AERONET) and the Multiangle Imaging SpectroRadiometer (MISR) in the 14 regions during 2008. In Southern Hemisphere Africa (SHAF) and South America (SHSA), where aerosols tend to be clearly dominated by smoke in September, the simulated AOD values were underestimated in almost all experiments compared to MISR, except for the QFED2.4 run in SHSA. The model-simulated AOD values based on FEER1.0 and QFED2.4 were the closest to the corresponding AERONET data, being, respectively, about 73 % and 100 % of the AERONET observed AOD at Alta Floresta in SHSA and about 49 % and 46 % at Mongu in SHAF. The simulated AOD based on the other four BB emission datasets accounted for only ∼50 % of the AERONET AOD at Alta Floresta and ∼20 % at Mongu. Overall, during the biomass burning peak seasons, at most of the selected AERONET sites in each region, the AOD values simulated with QFED2.4 were the highest and closest to AERONET and MISR observations, followed closely by FEER1.0. However, the QFED2.4 run tends to overestimate AOD in the region of SHSA, and the QFED2.4 BB emission dataset is tuned with the GEOS model. In contrast, the FEER1.0 BB emission dataset is derived in a more model-independent fashion and is more physically based since its emission coefficients are independently derived at each grid box. Therefore, we recommend the FEER1.0 BB emission dataset for aerosol-focused hindcast experiments in the two biomass-burning-dominated regions in the Southern Hemisphere, SHAF, and SHSA (as well as in other regions but with lower confidence). The differences between these six BB emission datasets are attributable to the approaches and input data used to derive BB emissions, such as whether AOD from satellite observations is used as a constraint, whether the approaches to parameterize the fire activities are based on burned area, FRP, or active fire count, and which set of emission factors is chosen.

Where’s the fire? Using in-situ observations from the NOAA/NASA FIREX-AQ campaign to validate small fire in the central and southern U.S.

2020 ◽  
Author(s):  
Eileen Rintsch ◽  
Jessica L. McCarty
Keyword(s):  
United States ◽  
Land Use ◽  
Infrared Imaging ◽  
The United States ◽  
Climate Impacts ◽  
Pollution Monitoring ◽  
Burned Area ◽  
Small Scale ◽  
Active Fire ◽  
Emissions Inventories

<p>Crop residue and rangeland burning is a common practice in the United States but verified ground-based estimates for the frequency of these fires is sparse. We present a comparison between known fire locations collected during the summer 2019 NOAA/NASA FIREX-AQ field campaign with several satellite-based active fire detections to estimate the occurrence of small-scale fires in agroecosystems. Many emissions inventories at the state-, country-, and global-level are driven by active fire detections and not burned area estimates for small fires in agroecosystems. The study area is focused on the southern Great Plains and Mississippi Delta of the United States. We combined fire occurrence data from 375 m Visible Infrared Imaging Spectrometer (VIIRS), 1 km Moderate Resolution Imaging Spectroradiometer (MODIS), and 2 km Geostationary Operational Environmental Satellite (GOES) active fires with 30 m land use data from U.S. Department of Agriculture Cropland Data Layer (CDL). The detections were compared to fires and land use validated in the field during the NOAA/NASA FIREX-AQ mission. GOES detected these fires at a higher frequency than MODIS or VIIRS. For example, MODIS detected 873 active fires and VIIRS detected 2,859, while GOES detected 13,634 active fires. Additionally, a large amount of the fires documented in the field, approximately 41%, were not detected by any satellite instrument used in the study. If GOES detections are excluded, approximately 5% of the documented fires were detected. This suggests that a large amount of cropland and rangeland burning are not detected by current active fire products from polar orbiting satellites like MODIS and VIIRS, with implications for regional air pollution monitoring, emissions inventories, and climate impacts of open burning.  </p>

scholarly journals On the use of ATSR fire count data to estimate the seasonal and interannual variability of vegetation fire emissions

2002 ◽  
Vol 2 (4) ◽  
pp. 1159-1179 ◽  
Author(s):  
M. G. Schultz
Keyword(s):  
Interannual Variability ◽  
Biomass Burning ◽  
Seasonal Pattern ◽  
Burned Area ◽  
Time Resolved ◽  
Fire Emissions ◽  
Seasonal And Interannual Variability ◽  
Active Fire ◽  
Time Period ◽  
Along Track

Abstract. Biomass burning has long been recognised as an important source of trace gases and aerosols in the atmosphere. The burning of vegetation has a repeating seasonal pattern, but the intensity of burning and the exact localisation of fires vary considerably from year to year. Recent studies have demonstrated the high interannual variability of the emissions that are associated with biomass burning. In this paper we present a methodology using active fire counts from the Along-Track Scanning Radiometer (ATSR) sensor on board the ERS-2 satellite to estimate the seasonal and interannual variability of global biomass burning emissions in the time period 1996--2000. From the ATSR data, we compute relative scaling factors of burning intensity for each month, which are then applied to a standard inventory for carbon monoxide emissions from biomass burning. The new, time-resolved inventory is evaluated using the few existing multi-year burned area observations on continental scales.

scholarly journals Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009)

2010 ◽  
Vol 10 (23) ◽  
pp. 11707-11735 ◽  
Author(s):  
G. R. van der Werf ◽  
J. T. Randerson ◽  
L. Giglio ◽  
G. J. Collatz ◽  
M. Mu ◽  
...  
Keyword(s):  
South America ◽  
Carbon Emissions ◽  
Agricultural Waste ◽  
Trace Gases ◽  
Plant Productivity ◽  
Tropical Deforestation ◽  
Burned Area ◽  
Fire Emissions ◽  
Active Fire ◽  
Peat Fires

Abstract. New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used maps of burned area derived from the Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and estimates of plant productivity derived from Advanced Very High Resolution Radiometer (AVHRR) observations during the same period. Average global fire carbon emissions according to this version 3 of the Global Fire Emissions Database (GFED3) were 2.0 Pg C year−1 with significant interannual variability during 1997–2001 (2.8 Pg C year−1 in 1998 and 1.6 Pg C year−1 in 2001). Globally, emissions during 2002–2007 were relatively constant (around 2.1 Pg C year−1) before declining in 2008 (1.7 Pg C year−1) and 2009 (1.5 Pg C year−1) partly due to lower deforestation fire emissions in South America and tropical Asia. On a regional basis, emissions were highly variable during 2002–2007 (e.g., boreal Asia, South America, and Indonesia), but these regional differences canceled out at a global level. During the MODIS era (2001–2009), most carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. Total carbon emissions were on average 13% lower than in our previous (GFED2) work. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C year−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

scholarly journals Six Global Biomass Burning Emission Datasets: Inter-comparison and Application in one Global Aerosol Model

2019 ◽  
Author(s):  
Xiaohua Pan ◽  
Charles Ichoku ◽  
Mian Chin ◽  
Huisheng Bian ◽  
Anton Darmenov ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Satellite Observations ◽  
Burned Area ◽  
Aerosol Model ◽  
Fire Emissions ◽  
Earth Observing System ◽  
Active Fire ◽  
Aerosol Emission ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
High Level

Abstract. Aerosols from biomass burning (BB) emissions are poorly constrained in global and regional models, resulting in a high level of uncertainty in understanding their impacts. In this study, we compared six BB aerosol emission datasets for 2008 globally as well as in 14 sub-regions. The six BB emission datasets are: (1) GFED3.1 (Global Fire Emissions Database version 3.1); (2) GFED4s (Global Fire Emissions Database version 4 with small fires); (3) FINN1.5 (Fire INventory from NCAR version 1.5); (4) GFAS1.2 (Global Fire Assimilation System version 1.2); (5) FEER1.0 (Fire Energetics and Emissions Research version 1.0), and (6) QFED2.4 (Quick Fire Emissions Dataset version 2.4). Although biomass burning emissions of aerosols from these six BB emission datasets showed similar spatial distributions, their global total emission amounts differed by a factor of 3–4, ranging from 13.76 to 51.93 Tg for organic carbon and from 1.65 to 5.54 Tg for black carbon. In most regions, QFED2.4 and FEER1.0, which are based on the satellite observations of fire radiative power (FRP) and utilize the aerosol optical depth (AOD) from the Moderate Resolution Imaging Spectroradiometer (MODIS), yielded higher BB emissions than the rest by a factor of 2–4. In comparison, the BB emission from GFED4s and GFED3.1, which are based on satellite retrieval of burned area and no AOD constraints, were at the low end of the range. In order to examine the sensitivity of model simulated AOD to the different BB emission datasets, we ingested these six BB emission datasets separately into the same global model, the NASA Goddard Earth Observing System (GEOS) model, and compared the simulated AOD with observed AOD from the AErosol RObotic NETwork (AERONET) and MODIS in 14 sub-regions during 2008. In Southern hemisphere Africa (SHAF) and South America (SHSA), where aerosols tend to be clearly dominated by smoke in September, the simulated AOD were underestimated in all experiments. More specifically, the model-simulated AOD based on FEER1.0 and QFED2.4 were the closest to the corresponding AERONET data, being about 73 % and 100 % of the AERONET observed AOD at Alta-Floresta in SHSA, 49 % and 46 % at Mongu in SHAF, respectively. The simulated AOD based on the other four BB emission datasets accounted for only ~ 50 % of the AERONET AOD at Alta Floresta and ~ 20 % of at Mongu. Overall, during the biomass burning peak seasons, at most of the selected AERONET sites in each region, the AOD simulated with QFED2.4 were the highest and closest to AERONET and MODIS observations, followed closely by FEER1.0. The differences between these six BB emission datasets are attributable to the approaches and input data used to derive BB emissions, such as whether AOD from satellite observations is used as a constraint, whether the approaches to parameterize the fire activities are based on burned area, FRP, or active fire count, and which set of emission factors is chosen.  

scholarly journals New fire diurnal cycle characterizations to improve fire radiative energy assessments made from MODIS observations

2015 ◽  
Vol 15 (15) ◽  
pp. 8831-8846 ◽  
Author(s):  
N. Andela ◽  
J. W. Kaiser ◽  
G. R. van der Werf ◽  
M. J. Wooster
Keyword(s):  
Diurnal Cycle ◽  
Radiative Energy ◽  
Burned Area ◽  
Sampled Data ◽  
Fire Event ◽  
Data Set ◽  
Study Region ◽  
Fire Emissions ◽  
Active Fire ◽  
Fire Activity

Abstract. Accurate near real time fire emissions estimates are required for air quality forecasts. To date, most approaches are based on satellite-derived estimates of fire radiative power (FRP), which can be converted to fire radiative energy (FRE) which is directly related to fire emissions. Uncertainties in these FRE estimates are often substantial. This is for a large part because the most often used low-Earth orbit satellite-based instruments such as the Moderate Resolution Imaging Spectroradiometer (MODIS) have a relatively poor sampling of the usually pronounced fire diurnal cycle. In this paper we explore the spatial variation of this fire diurnal cycle and its drivers using data from the geostationary Meteosat Spinning Enhanced Visible and Infrared Imager (SEVIRI). In addition, we sampled data from the SEVIRI instrument at MODIS detection opportunities to develop two approaches to estimate hourly FRE based on MODIS active fire detections. The first approach ignored the fire diurnal cycle, assuming persistent fire activity between two MODIS observations, while the second approach combined knowledge on the climatology of the fire diurnal cycle with active fire detections to estimate hourly FRE. The full SEVIRI time series, providing full coverage of the fire diurnal cycle, were used to evaluate the results. Our study period comprised of 3 years (2010–2012), and we focused on Africa and the Mediterranean basin to avoid the use of potentially lower quality SEVIRI data obtained at very far off-nadir view angles. We found that the fire diurnal cycle varies substantially over the study region, and depends on both fuel and weather conditions. For example, more "intense" fires characterized by a fire diurnal cycle with high peak fire activity, long duration over the day, and with nighttime fire activity are most common in areas of large fire size (i.e., large burned area per fire event). These areas are most prevalent in relatively arid regions. Ignoring the fire diurnal cycle generally resulted in an overestimation of FRE, while including information on the climatology of the fire diurnal cycle improved FRE estimates. The approach based on knowledge of the climatology of the fire diurnal cycle also improved distribution of FRE over the day, although only when aggregating model results to coarser spatial and/or temporal scale good correlation was found with the full SEVIRI hourly reference data set. We recommend the use of regionally varying fire diurnal cycle information within the Global Fire Assimilation System (GFAS) used in the Copernicus Atmosphere Monitoring Services, which will improve FRE estimates and may allow for further reconciliation of biomass burning emission estimates from different inventories.

scholarly journals Fire Detection and Fire Radiative Power in Forests and Low-Biomass Lands in Northeast Asia: MODIS versus VIIRS Fire Products

2020 ◽  
Vol 12 (18) ◽  
pp. 2870
Author(s):  
Yuyun Fu ◽  
Rui Li ◽  
Xuewen Wang ◽  
Yves Bergeron ◽  
Osvaldo Valeria ◽  
...  
Keyword(s):  
Infrared Imaging ◽  
Northeast Asia ◽  
Fire Detection ◽  
Fire Regimes ◽  
Burned Area ◽  
Commission Errors ◽  
Fire Emissions ◽  
Radiative Power ◽  
Moderate Resolution ◽  
Fire Radiative Power

Fire omission and commission errors, and the accuracy of fire radiative power (FRP) from satellite moderate-resolution impede the studies on fire regimes and FRP-based fire emissions estimation. In this study, we compared the accuracy between the extensively used 1-km fire product of MYD14 from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the 375-m fire product of VNP14IMG from the Visible Infrared Imaging Radiometer Suite (VIIRS) in Northeastern Asia using data from 2012–2017. We extracted almost simultaneous observation of fire detection and FRP from MODIS-VIIRS overlapping orbits from the two fire products, and identified and removed duplicate fire detections and corresponding FRP in each fire product. We then compared the performance of the two products between forests and low-biomass lands (croplands, grasslands, and herbaceous vegetation). Among fire pixels detected by VIIRS, 65% and 83% were missed by MODIS in forests and low-biomass lands, respectively; whereas associated omission rates by VIIRS for MODIS fire pixels were 35% and 53%, respectively. Commission errors of the two fire products, based on the annual mean measurements of burned area by Landsat, decreased with increasing FRP per fire pixel, and were higher in low-biomass lands than those in forests. Monthly total FRP from MODIS was considerably lower than that from VIIRS due to more fire omission by MODIS, particularly in low-biomass lands. However, for fires concurrently detected by both sensors, total FRP was lower with VIIRS than with MODIS. This study contributes to a better understanding of fire detection and FRP retrieval performance between MODIS and its successor VIIRS, providing valuable information for using those data in the study of fire regimes and FRP-based fire emission estimation.

scholarly journals On the use of ATSR fire count data to estimate the seasonal and interannual variability of vegetation fire emissions

2002 ◽  
Vol 2 (5) ◽  
pp. 387-395 ◽  
Author(s):  
M. G. Schultz
Keyword(s):  
Interannual Variability ◽  
Biomass Burning ◽  
Seasonal Pattern ◽  
Burned Area ◽  
Time Resolved ◽  
Fire Emissions ◽  
Seasonal And Interannual Variability ◽  
Active Fire ◽  
Time Period ◽  
Along Track

Abstract. Biomass burning has long been recognised as an important source of trace gases and aerosols in the atmosphere. The burning of vegetation has a repeating seasonal pattern, but the intensity of burning and the exact localisation of fires vary considerably from year to year. Recent studies have demonstrated the high interannual variability of the emissions that are associated with biomass burning. In this paper I present a methodology using active fire counts from the Along-Track Scanning Radiometer (ATSR) sensor on board the ERS-2 satellite to estimate the seasonal and interannual variability of global biomass burning emissions in the time period 1996--2000. From the ATSR data, I compute relative scaling factors of burning intensity for each month, which are then applied to a standard inventory for carbon monoxide emissions from biomass burning. The new, time-resolved inventory is evaluated using the few existing multi-year burned area observations on continental scales.

scholarly journals Global fire emissions and the contribution of deforestation, savanna, forest, agricultural, and peat fires (1997–2009)

2010 ◽  
Vol 10 (6) ◽  
pp. 16153-16230 ◽  
Author(s):  
G. R. van der Werf ◽  
J. T. Randerson ◽  
L. Giglio ◽  
G. J. Collatz ◽  
M. Mu ◽  
...  
Keyword(s):  
South America ◽  
Carbon Emissions ◽  
Agricultural Waste ◽  
Trace Gases ◽  
Plant Productivity ◽  
Tropical Deforestation ◽  
Burned Area ◽  
Fire Emissions ◽  
Active Fire ◽  
Peat Fires

Abstract. New burned area datasets and top-down constraints from atmospheric concentration measurements of pyrogenic gases have decreased the large uncertainty in fire emissions estimates. However, significant gaps remain in our understanding of the contribution of deforestation, savanna, forest, agricultural waste, and peat fires to total global fire emissions. Here we used a revised version of the Carnegie-Ames-Stanford-Approach (CASA) biogeochemical model and improved satellite-derived estimates of area burned, fire activity, and plant productivity to calculate fire emissions for the 1997–2009 period on a 0.5° spatial resolution with a monthly time step. For November 2000 onwards, estimates were based on burned area, active fire detections, and plant productivity from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. For the partitioning we focused on the MODIS era. We used burned area estimates based on Tropical Rainfall Measuring Mission (TRMM) Visible and Infrared Scanner (VIRS) and Along-Track Scanning Radiometer (ATSR) active fire data prior to MODIS (1997–2000) and Advanced Very High Resolution Radiometer (AVHRR) derived estimates of plant productivity during the same period. Average global fire carbon emissions were 2.0 Pg yr−1 with significant interannual variability during 1997–2001 (2.8 Pg yr−1 in 1998 and 1.6 Pg yr−1 in 2001). Emissions during 2002–2007 were relatively constant (around 2.1 Pg yr−1) before declining in 2008 (1.7 Pg yr−1) and 2009 (1.5 Pg yr−1) partly due to lower deforestation fire emissions in South America and tropical Asia. During 2002–2007, emissions were highly variable from year-to-year in many regions, including in boreal Asia, South America, and Indonesia, but these regional differences cancelled out at a global level. During the MODIS era (2001–2009), most fire carbon emissions were from fires in grasslands and savannas (44%) with smaller contributions from tropical deforestation and degradation fires (20%), woodland fires (mostly confined to the tropics, 16%), forest fires (mostly in the extratropics, 15%), agricultural waste burning (3%), and tropical peat fires (3%). The contribution from agricultural waste fires was likely a lower bound because our approach for measuring burned area could not detect all of these relatively small fires. For reduced trace gases such as CO and CH4, deforestation, degradation, and peat fires were more important contributors because of higher emissions of reduced trace gases per unit carbon combusted compared to savanna fires. Carbon emissions from tropical deforestation, degradation, and peatland fires were on average 0.5 Pg C yr−1. The carbon emissions from these fires may not be balanced by regrowth following fire. Our results provide the first global assessment of the contribution of different sources to total global fire emissions for the past decade, and supply the community with an improved 13-year fire emissions time series.

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